For the LCA models with just internalizing and externalizing disorders, in both the NCS and NCS-R samples, a 5-class model fit best according to BIC and AIC (see Table 1; note that AIC values level off after 5 classes for both models). For the LCA models with bipolar disorder, while the NCS revealed a 5-class solution again, in the NCS-R, the BIC indicated a 4-class model, while the AIC suggested a 5-class model. To reconcile this discrepancy, we examined bivariate residuals among disorders in this model (BVRs) [25], and employed the bootstrap likelihood ratio test (BLRT) [32] to formally assess the statistical significance of adding an extra class. BVRs indicate the strength of association between pairs of disorders, after accounting for those modeled by the latent classes; the presence of large BVRs in a model indicates that the model is not adequately capturing such associations. The BLRT evaluates the difference in log-likelihoods between two models by comparing it to an empirically estimated difference distribution generated by bootstrapping. An examination of BVRs among disorders in the 4-class model revealed several large
